| Autor: |
Sanaz Nazari-Farsani, Yannan Yu, Rui Duarte Armindo, Maarten Lansberg, David S. Liebeskind, Gregory Albers, Soren Christensen, Craig S. Levin, Greg Zaharchuk |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
NeuroImage: Clinical, Vol 37, Iss , Pp 103278- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2213-1582 |
| DOI: |
10.1016/j.nicl.2022.103278 |
| Popis: |
Background: For prognosis of stroke, measurement of the diffusion-perfusion mismatch is a common practice for estimating tissue at risk of infarction in the absence of timely reperfusion. However, perfusion-weighted imaging (PWI) adds time and expense to the acute stroke imaging workup. We explored whether a deep convolutional neural network (DCNN) model trained with diffusion-weighted imaging obtained at admission could predict final infarct volume and location in acute stroke patients. Methods: In 445 patients, we trained and validated an attention-gated (AG) DCNN to predict final infarcts as delineated on follow-up studies obtained 3 to 7 days after stroke. The input channels consisted of MR diffusion-weighted imaging (DWI), apparent diffusion coefficients (ADC) maps, and thresholded ADC maps with values less than 620 × 10−6 mm2/s, while the output was a voxel-by-voxel probability map of tissue infarction. We evaluated performance of the model using the area under the receiver-operator characteristic curve (AUC), the Dice similarity coefficient (DSC), absolute lesion volume error, and the concordance correlation coefficient (ρc) of the predicted and true infarct volumes. Results: The model obtained a median AUC of 0.91 (IQR: 0.84–0.96). After thresholding at an infarction probability of 0.5, the median sensitivity and specificity were 0.60 (IQR: 0.16–0.84) and 0.97 (IQR: 0.93–0.99), respectively, while the median DSC and absolute volume error were 0.50 (IQR: 0.17–0.66) and 27 ml (IQR: 7–60 ml), respectively. The model’s predicted lesion volumes showed high correlation with ground truth volumes (ρc = 0.73, p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
